At a Glance
- Tasks: Validate and benchmark ML systems to ensure reliable AI performance.
- Company: Join Graphcore, a leader in AI technology with a collaborative culture.
- Benefits: Enjoy unlimited leave, matched pension, equity options, and flexible work arrangements.
- Other info: Inclusive environment with opportunities for personal and professional growth.
- Why this job: Dive deep into AI systems and make a real impact on cutting-edge technology.
- Qualifications: Strong ML experience, Python skills, and a passion for system performance.
The predicted salary is between 70000 - 90000 £ per year.
Validate the ML stack that turns accelerator hardware into trusted AI performance. This role sits where modern ML models meet Graphcore’s software and hardware stack. You will test, benchmark and validate complex systems before they reach customers. Your work will expose regressions, correctness issues and performance limits across frameworks, models and execution environments. You will help teams understand what is working, what is breaking and why. You will run open source models, build automated benchmarking pipelines and create targeted tests for low level ML behaviour. That includes numerical precision, quantisation, attention mechanisms, distributed execution and model subgraphs. This is a role for someone who wants to stay close to how AI systems really work. You will not design new models, but you will make them run reliably on ambitious infrastructure.
The ML QA team is where Graphcore’s ML software stack comes together for validation. Work spans unit tests, full model benchmarks, distributed workloads, simulators, emulators and hardware targets. Engineers are expected to take ownership, question assumptions and improve how testing is done. The team moves quickly, but decisions are grounded in evidence, benchmark data and technical discussion. You will work closely with software, infrastructure and hardware teams. Squads organise around priorities, with space for engineers to shape roadmaps and raise the quality bar.
What we’re looking for:
- Strong experience in Machine Learning or ML-adjacent software engineering roles.
- A solid grasp of neural networks, training, inference, numerical precision and performance trade-offs.
- Hands-on experience with PyTorch, TensorFlow, JAX, Triton or similar ML frameworks and tools.
- Strong Python skills for automation, experimentation, benchmarking and reporting.
- Experience designing, running and analysing ML benchmarks or model experiments.
- Confident debugging skills in Linux, with curiosity about model behaviour and system performance.
Benefits:
- Unlimited annual leave
- Up to 5% matched pension
- Phantom equity - share in Graphcore's success
- True flexibility in how and where you work
- Office spaces designed for collaboration
- Free food and an on-site barista
- Health cash plan
- Income protection
- Life assurance
- Along with other benefits you can choose from (private medical insurance, dental plan etc)
We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work. We’re an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we’re happy to support you.
Staff Engineer (ML Engineer) in Bristol employer: EngineersOfAI
Graphcore is an exceptional employer for those passionate about machine learning and AI, offering a dynamic work culture that encourages ownership and innovation. With benefits like unlimited annual leave, phantom equity, and true flexibility in work arrangements, employees thrive in an inclusive environment designed for collaboration and personal growth. The opportunity to work closely with cutting-edge technology and cross-functional teams makes this role not just a job, but a meaningful career path in the heart of the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Engineer (ML Engineer) in Bristol
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We think you need these skills to ace Staff Engineer (ML Engineer) in Bristol
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Prepare for Case Studies
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